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goes

GOES Reader

GOESReader

Bases: GriddedReader

Reader for GOES-R Series (GOES-16, 17, 18) ABI data. Supports local files and S3 (via s3fs).

Source code in monetio/readers/goes.py 
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@register_reader("goes")
class GOESReader(GriddedReader):
    """
    Reader for GOES-R Series (GOES-16, 17, 18) ABI data.
    Supports local files and S3 (via s3fs).
    """

    def open_dataset(
        self,
        files: str | list[str] = None,
        dates: pd.DatetimeIndex | list[datetime.datetime] | datetime.datetime | str = None,
        satellite: str = "16",
        product: str = "ABI-L2-AODF",
        **kwargs,
    ) -> xr.Dataset:
        """
        Reads GOES data.

        Parameters
        ----------
        files : Union[str, List[str]], optional
            File path(s) or URL(s).
        dates : Union[pd.DatetimeIndex, List[datetime], datetime, str], optional
            Dates to retrieve. If files is None, this is used to build URLs.
        satellite : str, optional
            Satellite identifier (e.g., '16', '17', '18'). Default is '16'.
        product : str, optional
            GOES product (e.g., 'ABI-L2-AODF'). Default is 'ABI-L2-AODF'.
        **kwargs : dict
            Additional arguments passed to XarrayDriver.open.

        Returns
        -------
        xr.Dataset
            The GOES dataset.
        """
        if files is None:
            if dates is None:
                raise ValueError("Either 'files' or 'dates' must be provided.")
            files = self.build_urls(dates, satellite=satellite, product=product)

        if "preprocess" not in kwargs:
            kwargs["preprocess"] = goes_preprocess

        if "engine" not in kwargs:
            kwargs["engine"] = "h5netcdf"

        ds = super().open_dataset(files, **kwargs)

        # Update history
        ds = update_history(ds, f"Read GOES-{satellite} {product} data.")

        return ds

    def harmonize(self, ds: xr.Dataset) -> xr.Dataset:
        """
        Apply GOES-specific naming conventions and metadata standardization.

        The heavy lifting is done in ``goes_preprocess`` which is passed as
        the ``preprocess`` callback to the driver.  This method applies any
        final dataset-level harmonization after files have been merged.

        Parameters
        ----------
        ds : xr.Dataset
            Input dataset (already preprocessed per-file).

        Returns
        -------
        xr.Dataset
            Harmonized dataset.
        """
        return super().harmonize(ds)

    def build_urls(
        self,
        dates: pd.DatetimeIndex | list[datetime.datetime] | datetime.datetime | str,
        satellite: str = "16",
        product: str = "ABI-L2-AODF",
    ) -> list[str]:
        """
        Build S3 URLs for GOES data based on dates.

        Parameters
        ----------
        dates : Union[pd.DatetimeIndex, List[datetime], datetime, str]
            Dates to retrieve.
        satellite : str, optional
            Satellite identifier ('16', '17', '18').
        product : str, optional
            GOES product.

        Returns
        -------
        List[str]
            List of S3 URLs.
        """
        from ..util import _import_required

        s3fs = _import_required("s3fs")

        if isinstance(dates, str | datetime.datetime | pd.Timestamp):
            dates = pd.DatetimeIndex([pd.to_datetime(dates)])
        else:
            dates = pd.to_datetime(dates)

        fs = s3fs.S3FileSystem(anon=True)
        bucket = f"noaa-goes{satellite}"

        urls = []
        for d in dates:
            # GOES S3 structure: <product>/<year>/<day_of_year>/<hour>/
            prefix = f"{bucket}/{product}/{d.strftime('%Y/%j/%H')}/"
            try:
                found = fs.ls(prefix)
                if not found:
                    continue

                # Find the file closest to the requested time
                file_dates = [
                    pd.to_datetime(f.split("_")[-1].split(".")[0][1:], format="%Y%j%H%M%S%f")
                    for f in found
                ]
                idx = np.argmin([abs(fd - d) for fd in file_dates])
                urls.append(f"s3://{found[idx]}")
            except (FileNotFoundError, ValueError):
                continue

        return sorted(list(set(urls)))

build_urls(dates, satellite='16', product='ABI-L2-AODF')

Build S3 URLs for GOES data based on dates.

Parameters:

Name Type Description Default
dates Union[DatetimeIndex, List[datetime], datetime, str]

Dates to retrieve.

 required
satellite str

Satellite identifier ('16', '17', '18').

 '16'
product str

GOES product.

 'ABI-L2-AODF'

Returns:

Type Description
List[str]

List of S3 URLs.
Source code in monetio/readers/goes.py 
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def build_urls(
    self,
    dates: pd.DatetimeIndex | list[datetime.datetime] | datetime.datetime | str,
    satellite: str = "16",
    product: str = "ABI-L2-AODF",
) -> list[str]:
    """
    Build S3 URLs for GOES data based on dates.

    Parameters
    ----------
    dates : Union[pd.DatetimeIndex, List[datetime], datetime, str]
        Dates to retrieve.
    satellite : str, optional
        Satellite identifier ('16', '17', '18').
    product : str, optional
        GOES product.

    Returns
    -------
    List[str]
        List of S3 URLs.
    """
    from ..util import _import_required

    s3fs = _import_required("s3fs")

    if isinstance(dates, str | datetime.datetime | pd.Timestamp):
        dates = pd.DatetimeIndex([pd.to_datetime(dates)])
    else:
        dates = pd.to_datetime(dates)

    fs = s3fs.S3FileSystem(anon=True)
    bucket = f"noaa-goes{satellite}"

    urls = []
    for d in dates:
        # GOES S3 structure: <product>/<year>/<day_of_year>/<hour>/
        prefix = f"{bucket}/{product}/{d.strftime('%Y/%j/%H')}/"
        try:
            found = fs.ls(prefix)
            if not found:
                continue

            # Find the file closest to the requested time
            file_dates = [
                pd.to_datetime(f.split("_")[-1].split(".")[0][1:], format="%Y%j%H%M%S%f")
                for f in found
            ]
            idx = np.argmin([abs(fd - d) for fd in file_dates])
            urls.append(f"s3://{found[idx]}")
        except (FileNotFoundError, ValueError):
            continue

    return sorted(list(set(urls)))

harmonize(ds)

Apply GOES-specific naming conventions and metadata standardization.

The heavy lifting is done in goes_preprocess which is passed as the preprocess callback to the driver. This method applies any final dataset-level harmonization after files have been merged.

Parameters:

Name Type Description Default
ds Dataset

Input dataset (already preprocessed per-file).

 required

Returns:

Type Description
Dataset

Harmonized dataset.
Source code in monetio/readers/goes.py 
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def harmonize(self, ds: xr.Dataset) -> xr.Dataset:
    """
    Apply GOES-specific naming conventions and metadata standardization.

    The heavy lifting is done in ``goes_preprocess`` which is passed as
    the ``preprocess`` callback to the driver.  This method applies any
    final dataset-level harmonization after files have been merged.

    Parameters
    ----------
    ds : xr.Dataset
        Input dataset (already preprocessed per-file).

    Returns
    -------
    xr.Dataset
        Harmonized dataset.
    """
    return super().harmonize(ds)

open_dataset(files=None, dates=None, satellite='16', product='ABI-L2-AODF', **kwargs)

Reads GOES data.

Parameters:

Name Type Description Default
files Union[str, List[str]]

File path(s) or URL(s).

 None
dates Union[DatetimeIndex, List[datetime], datetime, str]

Dates to retrieve. If files is None, this is used to build URLs.

 None
satellite str

Satellite identifier (e.g., '16', '17', '18'). Default is '16'.

 '16'
product str

GOES product (e.g., 'ABI-L2-AODF'). Default is 'ABI-L2-AODF'.

 'ABI-L2-AODF'
**kwargs dict

Additional arguments passed to XarrayDriver.open.

 {}

Returns:

Type Description
Dataset

The GOES dataset.
Source code in monetio/readers/goes.py 
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def open_dataset(
    self,
    files: str | list[str] = None,
    dates: pd.DatetimeIndex | list[datetime.datetime] | datetime.datetime | str = None,
    satellite: str = "16",
    product: str = "ABI-L2-AODF",
    **kwargs,
) -> xr.Dataset:
    """
    Reads GOES data.

    Parameters
    ----------
    files : Union[str, List[str]], optional
        File path(s) or URL(s).
    dates : Union[pd.DatetimeIndex, List[datetime], datetime, str], optional
        Dates to retrieve. If files is None, this is used to build URLs.
    satellite : str, optional
        Satellite identifier (e.g., '16', '17', '18'). Default is '16'.
    product : str, optional
        GOES product (e.g., 'ABI-L2-AODF'). Default is 'ABI-L2-AODF'.
    **kwargs : dict
        Additional arguments passed to XarrayDriver.open.

    Returns
    -------
    xr.Dataset
        The GOES dataset.
    """
    if files is None:
        if dates is None:
            raise ValueError("Either 'files' or 'dates' must be provided.")
        files = self.build_urls(dates, satellite=satellite, product=product)

    if "preprocess" not in kwargs:
        kwargs["preprocess"] = goes_preprocess

    if "engine" not in kwargs:
        kwargs["engine"] = "h5netcdf"

    ds = super().open_dataset(files, **kwargs)

    # Update history
    ds = update_history(ds, f"Read GOES-{satellite} {product} data.")

    return ds

goes_preprocess(ds)

Preprocess GOES dataset: calculate grid and standardize coordinates.

Parameters:

Name Type Description Default
ds Dataset

Input dataset.

 required

Returns:

Type Description
Dataset

Processed dataset.

Examples:

>>> ds = reader.open_dataset(files)
>>> ds = goes_preprocess(ds)
Source code in monetio/readers/goes.py 
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def goes_preprocess(ds: xr.Dataset) -> xr.Dataset:
    """
    Preprocess GOES dataset: calculate grid and standardize coordinates.

    Parameters
    ----------
    ds : xr.Dataset
        Input dataset.

    Returns
    -------
    xr.Dataset
        Processed dataset.

    Examples
    --------
    >>> ds = reader.open_dataset(files)
    >>> ds = goes_preprocess(ds)
    """
    # 1. Standardize dimensions and coordinates
    ds = standardize_satellite_coords(ds)

    # 2. Add time coordinate if not present
    if "time" not in ds.coords:
        ds = add_time_coord(ds, time_attr="time_coverage_start")

    # 3. Calculate Latitude/Longitude (Lazy)
    if "latitude" not in ds.coords and "goes_imager_projection" in ds.variables:
        ds = _add_goes_latlon(ds)

    # Update history
    ds = update_history(ds, "Preprocessed GOES data.")

    return ds